Investigating prior methodologies, it has come to our knowledge that in smart cities, a disaster management system needs an autonomous reasoning mechanism to efficiently enhance the situation awareness of disaster sites and reduce its after-effects. Disasters are unavoidable events that occur at anytime and anywhere. Timely response to hazardous situations can save countless lives. Therefore, this paper introduces a multi-agent system (MAS) with a situation-awareness method utilizing NB-IoT, cyan industrial Internet of things (IIOT), and edge intelligence to have efficient energy, optimistic planning, range flexibility, and handle the situation promptly. We introduce the belief-desire-intention (BDI) reasoning mechanism in a MAS to enhance the ability to have disaster information when an event occurs and perform an intelligent reasoning mechanism to act efficiently in a dynamic environment. Moreover, we illustrate the framework using a case study to determine the working of the proposed system. We develop ontology and a prototype model to demonstrate the scalability of our proposed system.
In this note, by using basic properties of the recently introduced concepts of generalized metric spaces, new conditions for the existence of a fixed point for weakly type contractive operator which sends a closed subset into the ambient space under consideration are examined. Our obtained result extends and unifies its corresponding ideas in metric and modular spaces. A comparative non-trivial example is provided to show the novelty and preeminence of our proposed notion.
In the current study, Tin oxide (SnO2), Silver–Tin oxide (Ag–SnO2), and Ag–Bi–SnO2 nanoparticles (NPs) were successfully synthesized using methanolic seed extracts of Caesalpinia bonduc (C.bonduc) plants. The NPS were characterized by X-ray diffraction (XRD), scanning electron microscope (SEM), Surface area analysis (SAA), energy dispersive X-ray (EDX) analysis, and Fourier transmission infrared (FTIR). The synthesized photocatalyst's surface area was 210, 235, and 238 m²/g for SnO2 and Ag–SnO2, and Ag–Bi–SnO2, respectively. The catalyst showed excellent activity for the degradation of MB dye in an aqueous medium. The results confirmed that the Ag–Bi–SnO2 exhibited 94% degradation of dye compared to Ag–SnO2 (90%) and SnO2(80%) under the same reaction conditions. Adding Ag and bismuth can also increase the degradation mechanism by preventing recombining electron-hole pairs. The report is novel, as no report to date has been published for the synthesis of Ag–Bi–SnO2, Ag–SnO2, and SnO2 NPs synthesized by C. bonduc seed extract; the procedure is simple, cheaper, and non-toxic compared to other methods employed for the synthesis of NPs. Eley-Rideal (ER) type of reaction mechanism was found to follow the degradation of MB dye in an aqueous medium.
Various N- and S-containing 5-membered heterocycles such as imidazole-2-thiones, thiazolidinones and thiazolidin-2-imines are among the most eminent biologically active organic heterocycles and are present in many marketed drugs. In view of their synthetic and biological significance, an efficient synthesis of two novel thiazolidine-2-imines (4a-b) utilizing a three-component one-pot approach starting from an aldimine, an alkyne and isothiocyanates has been developed. The reaction proceeded via a 5-exo digonal (5-exo dig) cyclization of a propargyl thiourea, formed in situ in the presence of Zn(II)-catalyst. The structures of the resulting products are elucidated by spectroscopic methods and X-ray crystallography. A DFT study explored the structural, thermodynamic and molecular electrostatic potential parameters for the compounds. The newly synthesized compounds (4a & 4b) were evaluated for the inhibition of tyrosinase both in vitro and in silico. The in vitro results revealed that the synthesized thiazolidine-2-imines (4a-b) showed good inhibition activity towards mushroom tyrosinase (IC50 = 1.151 ± 1.25 and 2.079 ± 0.87 μM respectively) in comparison to the kojic acid standard (IC50 = 16.031 ± 1.27 μM) a commonly used anti-pigment agent in plant and animal tissues. The experimental inhibition was further assessed by molecular docking studies between synthesized ligands and the human tyrosinase protein complex to investigate the intermolecular interactions responsible for tyrosinase inhibition activity.
The gaps between the complex nature of cancer and therapeutics have been narrowed down due to extensive research in molecular oncology. Despite gathering massive insight into the mysteries of tumor heterogeneity and the molecular framework of tumor cells, therapy resistance and adverse side effects of current therapeutic remain the major challenge. This has shifted the attention towards therapeutics with less toxicity and high efficacy. Myricetin a natural flavonoid has been under the spotlight for its anti-cancer, anti-oxidant, and anti-inflammatory properties. The cutting-edge molecular techniques have shed light on the interplay between myricetin and dysregulated signaling cascades in cancer progression, invasion, and metastasis. However, there are limited data available regarding the nano-delivery platforms composed of myricetin in cancer. In this review, we have provided a comprehensive detail of myricetin-mediated regulation of different cellular pathways, its implications in cancer prevention, preclinical and clinical trials, and its current available nano-formulations for the treatment of various cancers.
Honey is one of the best nutritious substances in the world, having different services in the body functions regulation. Ten elements (K, Na, Ca, Co, Cr, Mn, Mo, Ni, Pb, Se) from honey samples were analyzed from 80 different locations of Punjab and ten floras. The aim of the present study was to determine the quality and quantity of minerals and Physico-chemical analysis in honey. A flame photometer was used to measure the concentration of major minerals (K, Ca and Na). The concentration of micro minerals (Co, Cr, Mn, Mo, Ni, Pb and Se) was analyzed using Atomic Absorption Spectrometer. The concentration of macro-elements obtained was as follow (in ppm): K (166-1732), Na (107-418) and Ca (07-99), while the concentration of microelements (in ppm) Co (1-2), Cr (>1), Mn (<1), Mo (1.818), Ni (1.911), Pb (<1) and Se (1.968). The most abundant minerals were potassium, calcium and sodium, ranging between 396-810.5, 17.5-640.63 and 169.88-238.62 ppm, respectively. However, the trace mineral elements of honey were obtained in the order of decreasing Se > Co > Ni > Pb > Cr > Mo > Mn. The findings showed that all the heavy metals like Co, Cr, Ni and Pb were present in trace amounts and close to International Honey Quality Standard. The result of given honey samples represented highest value of moisture (31.23%), color (80 mm pfund), pH (8.23), acidity (72.02 meq/kg), electrical conductivity (0.85 ms/cm) and ash contents (0.83%).
The sparse matrix–vector product (SpMV), considered one of the seven dwarfs (numerical methods of significance), is essential in high-performance real-world scientific and analytical applications requiring solution of large sparse linear equation systems, where SpMV is a key computing operation. As the sparsity patterns of sparse matrices are unknown before runtime, we used machine learning-based performance optimization of the SpMV kernel by exploiting the structure of the sparse matrices using the Block Compressed Sparse Row (BCSR) storage format. As the structure of sparse matrices varies across application domains, optimizing the block size is important for reducing the overall execution time. Manual allocation of block sizes is error prone and time consuming. Thus, we propose AAQAL, a data-driven, machine learning-based tool that automates the process of data distribution and selection of near-optimal block sizes based on the structure of the matrix. We trained and tested the tool using different machine learning methods—decision tree, random forest, gradient boosting, ridge regressor, and AdaBoost—and nearly 700 real-world matrices from 43 application domains, including computer vision, robotics, and computational fluid dynamics. AAQAL achieved 93.47% of the maximum attainable performance with a substantial difference compared to in practice manual or random selection of block sizes. This is the first attempt at exploiting matrix structure using BCSR, to select optimal block sizes for the SpMV computations using machine learning techniques.
Flexible power sources are critical to achieve the wide adoption of portable and wearable electronics. Herein, a facile and general strategy of fabricating a fibrous electrode was developed by 3D active coating technology, in which a stepping syringe with electrode paste was synchronously injected onto a rotating conductive wire, distinguished from the conventional direct-write 3D printing without a current collector. A series of such electrodes with different coating weight can be fabricated accurately and efficiently by adjusting critical process parameters following a set of derived equations. The demonstrated fibrous Zn-MnO2 battery with a high commercial ε-MnO2 loading of 14.9 mg cm-2 onto a stainless steel wire shows a reasonable energy density of 108 mWh cm-3, while the fiber-shaped supercapacitor with commercial porous graphene exhibits a high capacitance of 142.9 F g-1 and good durability for bending 10,000 cycles. This work constructs a bridge between materials and fiber-shaped electrodes for flexible energy storage devices.
Drought is a multifaceted climate phenomenon. Due to recent climate warming, the risk of drought has increased. Regional drought management requires accurate regional drought characterization to prepare early warning drought mitigation policies. Therefore, a more flexible and efficient procedure is necessary for characterizing drought at a regional level. This study provides a new spatiotemporal weighting scheme for integrating precipitation data from various meteorological stations located in a specific region. Consequently, this article presents a new generalized regional drought indicator ‐ The Spatiotemporal Weighted Efficient Drought Index (STWEDI). The methodology of STWEDI consists of two stages: 1) the first stage combines the meteorological data of various stations located in a certain region under the proposed weighting scheme, and 2) the second stage standardizes the cumulative distribution function (CDF) of mixture probability models. In application, this research estimated the time series data of STWEDI of seven regions containing a varying number of meteorological stations. To assess the performance of STWEDI, we compared the time series data of STWEDI with the most commonly used Standardized Precipitation Index (SPI) using the Pearson correlation. Results show that STWEDI is strongly correlated with individual SPIs in all the clusters and scales. Moreover, we found that STWEDI is strongly associated with SPI at all time scales. These statistical measures show that STWEDI is the more effective drought indicator for regional drought monitoring.
In the past few years, two-dimensional (2D) layered nanomaterials have greatly attracted the scientifc community. Among 2D nanomaterials, the porphyrin-based Naphtalenic nanosheets have been the subject of intense research due to their utilization in photo-dynamic therapy and nanodevices. New technologies based on nanomaterials or Naphtalenic nanosheet are advantageous in overcoming the problems in conventional drug delivery like poor solubility, toxicity and poor release pattern of drugs. In chemical network theory, various molecular descriptors are used to predict the chemical properties of molecules; these molecular descriptors are found to be very useful for Quantitative Structure–Activity/ Quantitative Structure–Property (QSAR/QSPR) relationship analysis in materials engineering, chemical and pharmaceutical industries. Researchers have computed the molecular descriptors for various nanostructures; however, despite intense research, the topology of nanostructures is not yet well understood. Specially, to our knowledge, the computation of topological indices for the line graph of subdivision graph of H-Naphtalenic nanosheet has not been discussed so far, which may open new perspectives for a more accurate and reliable topological characterization of this nanosheet. In this article, we employed some important degree-based topological indices to study the chemical structure of Naphtalenic nanosheet as a chemical network for QSAR/QSPR analysis. We have computed these degree-based topological indices for the line graph of subdivision graph of H-Naphtalenic nanosheet and derived formulas for them. Based on the derived formulas, numerical results are obtained and the physical and chemical properties of the under study nanosheet are investigated.
Plant bioactive compounds, particularly apigenin, have therapeutic potential and functional activities that aid in the prevention of infectious diseases in many mammalian bodies and promote tumor growth inhibition. Apigenin is a flavonoid with low toxicities and numerous bioac-tive properties due to which it has been considered as a traditional medicine for decades. Apigenin shows synergistic effects in combined treatment with sorafenib in the HepG2 human cell line (HCC) in less time and statistically reduces the viability of tumor cells, migration, gene expression and apoptosis. The combination of anti-cancerous drugs with apigenin has shown health promoting potential against various cancers. It can prevent cell mobility, maintain the cell cycle and stimulate the immune system. Apigenin also suppresses mTOR activity and raises the UVB-induced phago-cytosis and reduces the cancerous cell proliferation and growth. It also has a high safety threshold, and active (anti-cancer) doses can be gained by consuming a vegetable and apigenin rich diet. Apig-enin also boosted autophagosome formation, decreased cell proliferation and activated autophagy by preventing the activity of the PI3K pathway, specifically in HepG2 cells. This paper provides an updated overview of apigenin's beneficial anti-inflammatory, antibacterial, antiviral, and anti-cancer effects, making it a step in the right direction for therapeutics. This study also critically analyzed the effect of apigenin on cancer cell signaling pathways including the PI3K/AKT/MTOR, JAK/STAT, NF-κB and ERK/MAPK pathways. Citation: Abid, R.; Ghazanfar, S.; Farid, A.; Sulaman, S.M.; Idrees, M.; Amen, R.A.; Muzammal, M.; Shahzad, M.K.; Mohamed, M.O.; Khaled, A.A.; et al. Pharmacological Properties of 4′, 5, 7-Trihydroxyflavone (Apigenin) and Its Impact on Cell Signaling Pathways. Molecules 2022, 27, 4304.
Despite global pandemic Chinese economic growth rate was 2.3 percent in 2020. GDP surpassed US $ 15 trillion and growth rate raised to 6.5 percent in fourth quarter of 2020 and US $ 17 trillion GDP was recorded in first quarter of 2021. People Republic China’s (PRC) gigantic military budget and revolution in military affairs (RMA) creates senese of hegemonic ambitions in its neighbours. Contrarily, United States (US) sights PRC has ambitions to expand its political influence, gain access to economic markets, change international order by replacing US. This potential asymmetrical and imbalanced relationship locks America in typical Thucydides trap. Washington reached conclusion that economic growth and military might are intertwined. However, it is dependent on China’s energy supplies. PRC’s rise can be slowed down by stopping or interrupting the flow of energy supplies. Range of threats are posed to PRC oil imports i.e. US aerial strike on PRC oil//gas pipelines, use of proxies specially ast Turkestan Islamic Movement (ETIM) to disrupt oil supplies, terrorist attacks on oil containers on land and naval blockade in Persian Gulf. The inference drawn is energy security dependent on Strait of Malacca is Achilles Heel of China. This paper aims at probing Washington’s capacity to disrupt or stop energy supplies to PRC in Malacca strait, Persian Gulf, land routes in Pakistan. It discusses various strategies including direct naval blockade, use of proxies and direct military strikes.
In recent years, water pollution has become a serious environmental issue. Accelerated globalization and modern lifestyle promotes the unconscious use of pharmaceutical and personal care products (PPCPs) (e.g., dyes, detergents, soaps, shampoos, antibiotics, medicines, household cleaning and so on). These compounds constitute a broad set of emerging pollutants with direct ingress into aquatic environments, precipitation on root surface iron plaque, absorption, and degradation by plants due to their high occurrence not only in seawater or wastewater treatment plants but also in drinking water. Novel and low-cost technologies for the extenuation of water contaminants are strongly required to satisfy the current demand of clean and freshwater. Intensive human interventions include the use of nanotechnology as efficient strategy to face this global challenge. The use of promising matrices-based nanotechnology can contribute to enhance the already existent strategies to monitor, prevent, and remove high-risk and toxic substances in water. Nanoadsorbent materials have been successfully used for water remediation approaches possess distinctive features in physiochemical properties, for instance, small size (1–100 nm) and high surface area, high catalyst activity and superior removal efficiency compared with bulk systems. This chapter presents an overview of the occurrence of potential contaminants in water and the use of nanoadsorbents with special emphasis in carbon-based and nanoparticle-based materials as contaminant mitigators in aqueous media.
Economic policies related to energy and the environment are found uncertain in developing economies. Renewable energy sources are gradually increasing in energy structure (ES) with the adoption of environment-related technologies (ERT). However, least attention is paid to investigating the nexus of economic policy uncertainty (EPU), ERT, ES, and ecological footprint (EF). Therefore, this study is an effort to examine the EPU, ERT, ES, and interaction of EPU and ERT on EF for BRICS economies under the umbrella of the STIRPAT model. By using the data from 1992 to 2020, findings are estimated through "cross-sectional dependence (CD test); CIPS and CADF unit root test; Westerlund's co-integration; and CS-ARDL, AMG, and CCEMG." Findings unveiled the negative role of EPU on EF. Furthermore, the role of RE and ERT is positive and substantial in decreasing the environmental degradation in BRICS. Therefore, the BRICS economies are suggested to be consistent on economic policies to catch the positive impact of ERT. Findings are robust to the policy implications.
For the HSI classification, the recently introduced nearest regularized subspace (NRS) classifier outperform the sparse representation-based classification (SRC) and collaborative representation-based classification (CRC). The NRS method has two major distance measurements parts to classify approximation of the testing simple properly. One is the residual between the approximation and the corresponding pixel, and the other is the elements in the Tikhonov matrix. The main contribution of this paper is to find the optimum distance measures for NRS to increase the performance results and minimize the running time compared to their previous versions and other existing methods. The experiments were conducted with four distance measures such as Manhattan distance (MD), Euclidean distance(ED), Chi-square (X²) and Cosine distance (CS). The different distance measures are implemented in residual and Tikhonov Matrix calculations. To sum up, sixteen (16) distance measurement combinations are tested on Four Datasets, such as Indian Pines, Pavia University, KSC and Center of Pavia. The experiments show higher accuracy and reduced time as compared to other methods, with NRS_X²-MD and NRS_MD-MD as the top two combinations.
Drought is recurrently occurring in many parts of the globe. In contrast to other natural hazards, drought has complex climatic characteristics. Several environmental factors are involved in the occurrence of drought hazards. However, the selection of an appropriate drought index may incorporate to make efficient drought mitigation policies. Moreover, the spatial distributions of extreme weather conditions (Dry/Wet) are necessary to avoid the consequences of future drought hazards. In this study, we aimed to explore and compare the regional profile of Dry/Wet episodes under various drought measures. Consequently, this research proposes a new spatial comparative procedure to assess and evaluate the spatial predictive distributions of Dry/Wet episodes under various drought measures. The study incorporates three Standardized Drought Indices (SDIs) and a spatial Poisson log-normal model to assess and evaluate the spatial predictive distributions of Dry/Wet episodes in Pakistan. Results of this study show that the segregated patterns of Dry/Wet counts are moderately consistent with the climatology of the region. However, the spatial patterns of Wet/Dry counts under various drought measures are significantly different under each index. Therefore, this research suggests the simultaneous use of multiple drought measures for accurate and precise drought monitoring at the regional level.
This article aims to determine the intervening strength of financial mindfulness between financial literacy and behavioural biases in women entrepreneurs. The literature has an enduring discussion regarding the profoundly unique financial behaviour of women. Financial literacy and behavioural biases constitute a recurrent research topic, yet how this nexus exists in the premise of women’s entrepreneurship is not well known. Building on this gap, we examined the impact of financial literacy on women entrepreneurs’ behavioural biases by focusing on financial mindfulness as a potential moderator. A random sample of 346 women entrepreneurs operating in Pakistan was analysed using structural equation modelling through AMOS 21. The results revealed a significant direct impact of financial literacy on reducing anchoring and herding bias; however, financial literacy was found to be unrelated to mental accounting bias. The moderation analysis further revealed interesting indirect impacts, such that financial literacy strongly reduced mental accounting and herding bias for financially mindful women. Nonetheless, financial mindfulness does not negatively catalyse the relationship between financial literacy and anchoring bias. By encompassing the concepts of financial literacy, mindfulness and behavioural biases, we offer a unique theoretical strand with practical implications for women entrepreneurs. We suggest new avenues for the longstanding dilemma related to the factors instigating suboptimal financial decision-making in women entrepreneurs in developing markets.
Shift photovoltaic current (SPC) in polar non-centrosymmetric materials has recently emerged as a promising candidate for the next generation of photovoltaic devices in which Shockley-Queisser limits are fully overcome. Here, we apply first-principles calculations to predict colossal SPC in the slide bilayers of 2D h-BN and β-GeS vdW homostructures. The large SPC in slide bilayers h-BN and β-GeS reaches 49.3 μAV⁻² and 130μ μAV⁻², respectively, in the ultra-violet (UV) region. Increasing the number of layers is further implemented to tune the band structure of the two homostructures. Consequently, giant SPC peaks about 3 times larger than those of the 2-layers are predicted at photon energies of 7.40 eV and 5.95 eV in the 5-layers of h-BN and β-GeS, respectively. The two homostructures may thus be promising building blocks for next-generation shift current devices. These findings also suggest layering as a possible convenient approach to enhancing and also tuning the SPC output in thin layered materials.
The development of nanofluid technology has become a key research area in physics, mathematics, engineering, and materials science. Nowadays, in many industrial applications, nanofluids are widely used to enhance thermophysical properties such as thermal diffusivity, thermal conductivity, and convective heat transfer. Scientists and engineers have established interests in the direction of flow problems developed via disk-shaped bodies. There are various logics to discuss flow phenomenon due to rotating bodies, but its applications include in thermal power engineering system, gas turbine rotors, air cleaning machines, aerodynamics, etc. Nowadays manufacturing industries have inaugurated to select liquid based on heat transfer properties. Therefore, this article focuses on studying the laminar incompressible nanofluid between two parallel disks. Mathematical formulations of the law of conservation of mass, momentum, and heat transfer are investigated numerically. By using suitable similarities, the flow equations are converted into nonlinear ordinary differential equations. The resulting equations were solved numerically via MATLAB software. The effects of physical parameters of interest, such as Reynolds number, magnetic factor, Brownian parameter, and thermophoresis parameter on normal velocity, streamwise velocity, temperature, and concentration profiles are computed and presented using the graphs. The results revealed that the energy profile significantly rises, and the profile moves closer to the upper disk by enhancing the Brownian motion and thermophoresis parameter. The dynamics behind this is that by increasing the Brownian motion, the boundary layer wideness increases which increases the temperature. Moreover, streamwise velocity increases for large values of Reynolds number. Besides, the thermophoresis profile increases for large values of the thermophoresis factor. It could be observed that shear stress at nonporous/porous disk is adjusted by selecting a suitable value of injection velocity at the porous disk. Also, normal velocity decreases by increasing the parameter M .
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